Finding novel ways to treat and cure diseases is a fundamental challenge in biomedical research. As reflected by the overall low clinical target validation success rate, there currently exists a general lack of reliable drug target prediction methods. Therefore, new bioinformatics screening approaches are required to accurately predict drug targets for a disease.
Novel drug targets refer to unexploited targets that can be used for developing first-in-class drugs and combination therapies. Network-based methods have been developed for the identification of unknown disease-associated genes.
How our Technology Works
To address this intrinsic challenge in drug discovery, InMed has developed a proprietary, in silico bioinformatics platform technology, which uses computer algorithms that can reach high-probability conclusions from massive, publicly available databases together with an internal library of cannabinoid drug information. This tool is a “network-based platform” for the identification of novel, plant-based therapies using: (i) comprehensive algorithms to integrate data from numerous bioinformatics databases, (ii) a database on the structure of previously researched pharmaceutical products, and (iii) an extensive database on over 200,000 phytochemicals, including cannabinoids.
Successes and Future Applications
Our bioinformatics platform has been integral to the identification of our target indications: INM-755 for the treatment of epidermolysis bullosa, INM-085 for the treatment of glaucoma, and INM-405 for the treatment of peripheral pain. In addition, it has also helped us compile a library of other opportunities that are currently earlier in the development pipeline.
InMed’s strategy for the continued advancement of the bioinformatics technology is to:Learn More